AMD Instinct MI250X

AMD Instinct MI250X

About GPU

The AMD Instinct MI250X is a professional-grade GPU that boasts impressive specs, making it an ideal choice for data centers and HPC (High-Performance Computing) applications. With a base clock of 1000MHz and a boost clock of 1700MHz, this GPU offers high clock speeds to handle complex workloads with ease. One of the standout features of the MI250X is its massive 128GB of HBM2e memory, providing ample storage for large datasets and complex computational tasks. The memory clock speed of 1600MHz ensures fast data transfer and access, further enhancing the GPU's performance. The MI250X also impresses with its 14080 shading units, enabling it to handle advanced graphics and parallel processing tasks efficiently. Additionally, the 16MB L2 cache helps to reduce latency and improve overall system performance. With a TDP of 500W, the MI250X is a power-hungry GPU, but its high theoretical performance of 47.87 TFLOPS more than justifies the power consumption. This GPU is designed to deliver exceptional computational power, making it well-suited for AI, machine learning, and other demanding workloads. Overall, the AMD Instinct MI250X is a powerhouse GPU that offers incredible performance and memory capacity, making it a compelling choice for professionals and organizations seeking top-tier computing capabilities. While its power requirements may be high, the MI250X excels in handling the most demanding workloads with speed and efficiency, making it a valuable asset in the realm of high-performance computing.

Basic

Label Name
AMD
Platform
Professional
Launch Date
November 2021
Model Name
Radeon Instinct MI250X
Generation
Radeon Instinct
Base Clock
1000MHz
Boost Clock
1700MHz
Bus Interface
PCIe 4.0 x16

Memory Specifications

Memory Size
128GB
Memory Type
HBM2e
Memory Bus
?
The memory bus width refers to the number of bits of data that the video memory can transfer within a single clock cycle. The larger the bus width, the greater the amount of data that can be transmitted instantaneously, making it one of the crucial parameters of video memory. The memory bandwidth is calculated as: Memory Bandwidth = Memory Frequency x Memory Bus Width / 8. Therefore, when the memory frequencies are similar, the memory bus width will determine the size of the memory bandwidth.
8192bit
Memory Clock
1600MHz
Bandwidth
?
Memory bandwidth refers to the data transfer rate between the graphics chip and the video memory. It is measured in bytes per second, and the formula to calculate it is: memory bandwidth = working frequency × memory bus width / 8 bits.
3277 GB/s

Theoretical Performance

Pixel Rate
?
Pixel fill rate refers to the number of pixels a graphics processing unit (GPU) can render per second, measured in MPixels/s (million pixels per second) or GPixels/s (billion pixels per second). It is the most commonly used metric to evaluate the pixel processing performance of a graphics card.
0 MPixel/s
Texture Rate
?
Texture fill rate refers to the number of texture map elements (texels) that a GPU can map to pixels in a single second.
1496 GTexel/s
FP16 (half)
?
An important metric for measuring GPU performance is floating-point computing capability. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy.
383.0 TFLOPS
FP64 (double)
?
An important metric for measuring GPU performance is floating-point computing capability. Double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy, while single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
47.87 TFLOPS
FP32 (float)
?
An important metric for measuring GPU performance is floating-point computing capability. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
46.913 TFLOPS

Miscellaneous

Shading Units
?
The most fundamental processing unit is the Streaming Processor (SP), where specific instructions and tasks are executed. GPUs perform parallel computing, which means multiple SPs work simultaneously to process tasks.
14080
L1 Cache
16 KB (per CU)
L2 Cache
16MB
TDP
500W

Benchmarks

FP32 (float)
Score
46.913 TFLOPS

Compared to Other GPU

FP32 (float) / TFLOPS
63.322 +35%
52.326 +11.5%
42.15 -10.2%
37.75 -19.5%